MicroRNAs (miRNAs) play essential roles in cell differentiation, development, gene regulation, and apoptosis, and have been widely implicated in numerous disease mechanisms. Owing to their regulatory importance, miRNAs are increasingly recognized as valuable disease biomarkers. Previous studies have used nucleotide sequence pairwise distances between miRNAs to explore disease associations and have derived the distribution of pairwise distances to assess the percentile rank of an observed miRNA pair. However, because a single disease may involve multiple miRNA biomarkers, evaluating the percentile rank of an average pairwise distance is often more appropriate than focusing on individual pairs. In this study, we established percentile distributions for the average pairwise nucleotide distances corresponding to different numbers of miRNAs. Applying this framework to 51 diseases and several groups of related diseases, we observed that miRNA biomarkers associated with the same disease, as well as with related diseases, often exhibit low-percentile average pairwise distances under the reference distribution. While the present study does not directly evaluate whether precursor miRNA (pre-miRNA) sequence similarity is associated with shared biological function or regulatory targets, the proposed framework provides a systematic approach for quantifying such similarity among disease-associated miRNAs and may serve as a useful foundation for future studies integrating functional and clinical validation.
Wang et al. (Thu,) studied this question.